The productivity of plants is considerably affected by various environmental stresses. Exploring the specific pattern of the near-infrared spectral data acquired non-destructively from plants subjected to stress can contribute to a better understanding of biophysical and biochemical processes in plants. Experiments for investigating NIR spectra of maize plants subjected to water stress were conducted. Two maize lines were used: US corn-belt inbred line B37 and mutant inbred XM 87-136, characterized by very high drought tolerance. After reaching the 4-leaf stage, 10 plants from each line were subjected to water stress, and 10 plants were used as control, kept under a regular water regime. The drought lasted until day 17 and then the plants were recovered by watering for 4 days. A MicroNIR OnSite-W Spectrometer (VIAVI Solutions Inc., Chandler, AZ, USA) was used for in vivo measurement of each maize leaf spectra. PLS models for determining drought days were created and aquagrams were calculated separately for the plants’ second, third, and fourth leaves. Differences in absorption spectra were observed between control, stressed, and recovered maize plants, as well as between different measurement days of stressed plants. Aquagrams were used to visualize the water spectral pattern in maize leaves and how it changes along the drought process.

The main objective of this study was to evaluate the possibilities of visible-near-infrared spectroscopy for investigating water and nitrogen stress in tomato plants. Two varieties of tomato plants (Red Bounty and Manusa) were grown in a greenhouse. Plants were divided into three groups: control, reduced nitrogen fertilization, and reduced watering. Spectral measurements of tomato leaves were made on-site. A USB4000 spectrometer for 450–1100 nm and a handheld AlbaNIR for the 900–1650 nm region were used for the spectra acquisition. Twenty-four vegetative indices were calculated using the reflectance characteristics of plants. Soft Independent Modeling of Class Analogy (SIMCA) models were developed for classification. Additionally, aquagrams were calculated. Results show differences between the spectra of leaves from control and stressed plants for both tomato varieties. Aquagrams clearly show the differences in water structures in the three groups of plants. The performance of developed SIMCA models for discriminating plants according to growing conditions was very high. The total accuracy was between 86.89% and 97.09%. Several vegetation indices successfully differentiate control and stressed plants for both tomato varieties. The results show successful differentiation of the control and stressed tomato plants based on spectral characteristics of the plants’ leaves in the visible and near-infrared region.

Purslane (Portulaca oleracea L.) has been regaining its reputation as a valuable food and source of nutrients and biologically active compounds, but a high content of oxalates reduces mineral bioavailability and poses nutritional limitations. This study evaluated the influence of culinary processing on oxalate content in purslane and the potential of near-infrared (NIR) spectroscopy for non-destructive assessment of total oxalates, ascorbic acid, and total organic acid. The ascorbic acid and total organic acid in fresh samples, and the total oxalate content of fresh, blanched, and pickled samples were determined. Culinary treatments (blanching and pickling) reduced oxalate content. The highest oxalate content was observed in fresh samples (33.38–61.84 g/100 g), lower in blanched samples (19.07–34.36 g/100 g), and the lowest content in pickling samples (10.48–18.31 g/100 g). NIR spectra (900–1700 nm) of the analyzed samples were measured, and PLS regression was used for the determination of tested components. The NIR spectroscopy achieved high predictive accuracy for ascorbic acid, total organic acid, and oxalate content. Rcval > 0.98 and SECV values between 0.02 and 0.38 g/100 g for oxalate content. NIR spectroscopy provides a rapid, accurate, and non-destructive alternative to conventional methods for oxalate determination in fresh, blanched, and pickled plant tissues, ascorbic acid and organic acid in fresh samples.

Low temperatures have a significant impact on the growth, development, and productivity of cucumber plants. The potential of near-infrared spectroscopy and the aquaphotomics approach for investigating chilling stress was studied in Voreas F1 and Gergana cultivars. Changes in the spectral patterns of cucumber plants were compared with physiological and metabolic data. Voreas plants were unable to survive seven days of low-temperature stress due to a drastic increase in electrolyte leakage and a decrease in the net photosynthesis rate, stomatal conductance, and transpiration rate. Gergana plants survived chilling by preserving cell membrane integrity and photosynthesis efficiency. During chilling treatment, the content of most metabolites in both cultivars was reduced compared to the controls, yet it was much more pronounced in Voreas. We observed an increased accumulation of cinnamic acid on the seventh day only in the Gergana cultivar. A MicroNIR spectrometer was used for in vivo spectral measurements of cotyledons and the first two leaves. Differences in absorption spectra were observed among control, stressed, and recovered plants, across different days of stress, and between the studied cultivars. The most significant differences were in the 1300–1600 nm range, much smaller for Gergana than Voreas. Aquagrams of the two cultivars also reveal differences in their responses to low temperatures and changes in water molecular structure in the leaves. The errors of prediction for the days of chilling by using PLS models were from 0.96 to 1.14 days for independent validation, depending on the spectral data of different leaves used. Near-infrared spectroscopy and aquaphotomics can be used as additional tools for early detection of stress and investigation of low-temperature tolerance in cucumber cultivars.

Non-destructive estimation of high-temperature stress effects on tobacco plants is crucial for both scientific research and practical applications. Normalized difference vegetation index (NDVI), chlorophyll index, and spectra in the range of 900–1700 nm of Burley, Oriental, and Virginia tobacco plants under control and high-temperature stress conditions were measured using portable instruments. NDVI and chlorophyll index measurements indicate that young leaves of all tobacco types are tolerant to high temperatures. In contrast, the older leaves (the fifth leaf) showed increased sensitivity to heat stress. The chlorophyll content of these leaves decreased by 40 to 60% after five days of stress, and by the seventh day, the reduction reached 80% or more in all plants. The vegetative index of the fifth leaf also decreased on the seventh day of stress in all tobacco types. Differences in near-infrared spectra were observed between control, stressed, and recovered plants, as well as among different stress days, and among tobacco lines. The most significant differences were in the 1300–1500 nm range. The first characterization of heat-induced changes in the molecular structure of water in tobacco leaves using an aquaphotomics approach was conducted. Models for determining days of high-temperature treatment based on near-infrared spectra achieved a standard error of cross-validation (SECV) from 0.49 to 0.62 days. The total accuracy of the Soft Independent Modeling of Class Analogy (SIMCA) classification models of control, stressed, and recovered plants ranged from 91.0 to 93.6% using leaves’ spectra of the first five days of high-temperature stress, and from 90.7 to 97.7% using spectra of only the fifth leaf. Similar accuracy was obtained using Partial Least Squares–Discriminant Analysis (PLS-DA). Near-infrared spectroscopy and aquaphotomics can be used as a fast and non-destructive approach for early detection of stress and additional tools for investigating high-temperature tolerance in tobacco plants.

This study explores a pilot multi-stage filtration system for treating irrigation water from Vaya Lake, heavily affected by anthropogenic pollution. Two filters were tested: one with natural zeolite (clinoptilolite) and another with biomass from the macrophyte Stuckenia pectinata . After a period of recirculation, there was a substantial decrease in total nitrogen, along with a noticeable reduction in nitrate nitrogen and orthophosphate. Additionally, the concentrations of aluminium, iron, sodium, calcium, and magnesium were significantly lowered, demonstrating effective removal of both nutrients and metals. Near-infrared (NIR) spectra (900–1650 nm) were measured, and partial least squares (PLS) models were developed to predict the content of pollutants. The determination accuracy of pollutants was very high. For each of the tested parameters, the correlation coefficient was higher than 0.94, and the determination errors were small. Aquagrams revealed changes in the water’s molecular structure, reflecting modifications in hydrogen-bonding networks. These findings show that combining multi-stage filtration with NIRS and aquaphotomics provides a rapid, non-invasive method for monitoring water purification, supporting sustainable reuse, and minimizing secondary pollution in impacted water bodies.